首页> 外文会议>Annual International Conference of the IEEE Engineering in Medicine and Biology Society >Characterizing muscular activities using non-negative matrix factorization from EMG channels for driver swings in golf
【24h】

Characterizing muscular activities using non-negative matrix factorization from EMG channels for driver swings in golf

机译:使用来自EMG通道的非负矩阵分解对高尔夫挥杆动作进行肌肉活动表征

获取原文
获取外文期刊封面目录资料

摘要

The goal of this study is to propose a data driven approach method to characterize muscular activities of complex actions in sports such as golf from a lot of EMG channels. Two problems occur in a many channel measurement. The first problem is that it takes a lot of time to check the many channel data because of combinatorial explosion. The second problem is that it is difficult to understand muscle activities related with complex actions. To solve these problems, we propose an analysis method of multi EMG channels using Non-negative Matrix Factorization and adopt the method to driver swings in golf. We measured 26 EMG channels about 4 professional coaches of golf. The results show that the proposed method detected 9 muscle synergies and the activation of each synergy were mostly fitted by sigmoid curve (R2=0.85).
机译:这项研究的目的是提出一种数据驱动的方法,以从许多EMG通道中表征高尔夫等运动中复杂动作的肌肉活动。在多通道测量中会出现两个问题。第一个问题是由于组合爆炸,需要花费大量时间来检查许多通道数据。第二个问题是很难理解与复杂动作有关的肌肉活动。为了解决这些问题,我们提出了一种使用非负矩阵分解的多EMG通道分析方法,并将该方法用于高尔夫球手挥杆。我们测量了大约4个职业高尔夫教练的26个EMG频道。结果表明,所提出的方法检测到9种肌肉协同作用,并且每种协同作用的激活大部分通过S形曲线拟合(R2 = 0.85)。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号